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Simulating a Virtual Machining Model in an Agent-Based Model for Advanced Analytics



David J. Lechevalier, Seungjun Shin, Sudarsan Rachuri, Sebti Foufou, Yung-Tsun T. Lee, Abdelaziz Bouras


Monitoring the performance of manufacturing equipment is critical to ensure the efficiency of manufacturing processes. Machine-monitoring data allows measuring manufacturing equipment efficiency. However, acquiring real and useful machine-monitoring data is expensive and time consuming. An alternative method of getting data is to generate machine-monitoring data using simulation. The simulated data can also be used to fill in real data set with missing values from real-time data collection. The mimic of real manufacturing systems in computer-based systems is called “virtual manufacturing”. The computer-based systems can execute the manufacturing system models that represent real manufacturing systems. In this paper, we introduce a virtual machining model of milling operations. We developed a prototype virtual machining model that represents 3-axis milling operations. This model is a digital mock-up of a real milling machine; it can generate machine-monitoring data from a process plan. The prototype model provides energy consumption data based on the physics-based equations. The model uses the standard interfaces of STEP-NC and MTConnect to represent process plan and machine-monitoring data, respectively. With machine-monitoring data for a given process plan, manufacturing engineers can anticipate the impact of a modification in their actual manufacturing systems. This paper describes how the virtual machining model is integrated into an agent-based model in a simulation environment. While facilitating the use of the virtual machining model, the agent-based model also contributes to the generation of more complex manufacturing system models, such as a virtual shop-floor model. The paper also describes initial model building steps towards such a shop-floor model. Aggregating data generated during the execution of a virtual shop-floor model will allow one to take advantage of data analytics techniques to predict performance at the shop-floor level.
Journal of Intelligent Manufacturing


STEP, MTConnect, milling operation, data generator, simulation, data analytics


Lechevalier, D. , Shin, S. , Rachuri, S. , Foufou, S. , Lee, Y. and Bouras, A. (2017), Simulating a Virtual Machining Model in an Agent-Based Model for Advanced Analytics, Journal of Intelligent Manufacturing, [online], (Accessed May 29, 2024)


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Created September 25, 2017, Updated June 2, 2021